gradFD is a MATLAB/OCTAVE's class which can be used for computing the derivatives and hessians of a function using finite differences. Many schemes have been implemented. Notice that the hessian computation remains incomplete and needs to be improved. Features gradFD is able to Compute derivatives with the following schemes forward and backward finite differences of order 1 to 5 (BDx and FDx with x={1,...,5}) central finite differences of order 2 to 8 (CDx with x={2,4,6,8}) Minimize the number of computations (especially the responses at the central points is done only one time) Use a specific stepsize in every direction Generate the set of sample points which can be used externally for computing responses. These responses can be loaded by the class in order to compute the gradients.